Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.

Reproducibility in the absence of selective reporting: An illustration from large-scale brain asymmetry research.

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Mitigating site effects in covariance for machine learning in neuroimaging data.

To acquire larger samples for answering complex questions in neuroscience, researchers have increasingly turned to multi-site neuroimaging studies. However, these studies are hindered by differences in images acquired across multiple sites. These effects have been shown to bias comparison between sites, mask biologically meaningful associations, and even introduce spurious associations. To address this, the field has focused on harmonizing data by removing site-related effects in the mean and variance of measurements. Contemporaneously with the increase in popularity of multi-center imaging, the use of machine learning (ML) in neuroimaging has also become commonplace. These approaches have been shown to provide improved sensitivity, specificity, and power due to their modeling the joint relationship across measurements in the brain. In this work, we demonstrate that methods for removing site effects in mean and variance may not be sufficient for ML. This stems from the fact that such methods fail to address how correlations between measurements can vary across sites. Data from the Alzheimer's Disease Neuroimaging Initiative is used to show that considerable differences in covariance exist across sites and that popular harmonization techniques do not address this issue. We then propose a novel harmonization method called Correcting Covariance Batch Effects (CovBat) that removes site effects in mean, variance, and covariance. We apply CovBat and show that within-site correlation matrices are successfully harmonized. Furthermore, we find that ML methods are unable to distinguish scanner manufacturer after our proposed harmonization is applied, and that the CovBat-harmonized data retain accurate prediction of disease group.

Generalizability and Transportability of the National Lung Screening Trial Data: Extending Trial Results to Different Populations.

BACKGROUND: Randomized controlled trials (RCT) play a central role in evidence-based healthcare. However, the clinical and policy implications of implementing RCTs in clinical practice are difficult to predict as the studied population is often different from the target population where results are being applied. This study illustrates the concepts of generalizability and transportability, demonstrating their utility in interpreting results from the National Lung Screening Trial (NLST). METHODS: Using inverse-odds weighting, we demonstrate how generalizability and transportability techniques can be used to extrapolate treatment effect from (i) a subset of NLST to the entire NLST population and from (ii) the entire NLST to different target populations. RESULTS: Our generalizability analysis revealed that lung cancer mortality reduction by LDCT screening across the entire NLST [16% (95% confidence interval [CI]: 4-24)] could have been estimated using a smaller subset of NLST participants. Using transportability analysis, we showed that populations with a higher prevalence of females and current smokers had a greater reduction in lung cancer mortality with LDCT screening [e.g., 27% (95% CI, 11-37) for the population with 80% females and 80% current smokers] than those with lower prevalence of females and current smokers. CONCLUSIONS: This article illustrates how generalizability and transportability methods extend estimation of RCTs' utility beyond trial participants, to external populations of interest, including those that more closely mirror real-world populations. IMPACT: Generalizability and transportability approaches can be used to quantify treatment effects for populations of interest, which may be used to design future trials or adjust lung cancer screening eligibility criteria.

Comparison of traveling-subject and ComBat harmonization methods for assessing structural brain characteristics.

Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and development. Measurement biases-caused by site differences in scanner/image-acquisition protocols-negatively influence the reliability and reproducibility of image-analysis methods. Harmonization can reduce bias and improve the reproducibility of multisite datasets. Herein, a traveling-subject (TS) dataset including 56 T1-weighted MRI scans of 20 healthy participants in three different MRI procedures-20, 19, and 17 subjects in Procedures 1, 2, and 3, respectively-was considered to compare the reproducibility of TS-GLM, ComBat, and TS-ComBat harmonization methods. The minimum participant count required for harmonization was determined, and the Cohen's d between different MRI procedures was evaluated as a measurement-bias indicator. The measurement-bias reduction realized with different methods was evaluated by comparing test-retest scans for 20 healthy participants. Moreover, the minimum subject count for harmonization was determined by comparing test-retest datasets. The results revealed that TS-GLM and TS-ComBat reduced measurement bias by up to 85 and 81.3%, respectively. Meanwhile, ComBat showed a reduction of only 59.0%. At least 6 TSs were required to harmonize data obtained from different MRI scanners, complying with the imaging protocol predetermined for multisite investigations and operated with similar scan parameters. The results indicate that TS-based harmonization outperforms ComBat for measurement-bias reduction and is optimal for MRI data in well-prepared multisite investigations. One drawback is the small sample size used, potentially limiting the applicability of ComBat. Investigation on the number of subjects needed for a large-scale study is an interesting future problem.

INSTRuCT: Protocol, Infrastructure, and Governance.

Background and Purpose: Very few large scale multicentric stroke clinical trials have been done in India. The Indian Council of Medical Research funded INSTRuCT (Indian Stroke Clinical Trial Network) as a task force project with the objectives to establish a state-of-the-art stroke clinical trial network and to conduct pharmacological and nonpharmacological stroke clinical trials relevant to the nation and globally. The purpose of the article is to enumerate the structure of multicentric stroke network, with emphasis on its scope, challenges and expectations in India. Methods: Multiple expert group meetings were conducted by Indian Council of Medical Research to understand the scope of network to perform stroke clinical trials in the country. Established stroke centers with annual volume of 200 patients with stroke with prior experience of conducting clinical trials were included. Central coordinating center, standard operating procedures, data and safety monitoring board were formed. Discussion: In first phase, 2 trials were initiated namely, SPRINT (Secondary Prevention by Structured Semi-Interactive Stroke Prevention Package in India) and Ayurveda treatment in the rehabilitation of patients with ischemic stroke in India (RESTORE [Rehabilitation of Ischemic stroke Patients in India: A Randomized controlled trial]). In second phase, 4 trials have been approved. SPRINT trial was the first to be initiated. SPRINT trial randomized first patient on April 28, 2018; recruited 3048 patients with an average of 128.5 per month so far. The first follow-up was completed on May 27, 2019. RESTORE trial randomized first patient on May 22, 2019; recruited 49 patients with an average of 3.7 per month so far. The first follow-up was completed on August 30, 2019. Conclusions: In next 5 years, INSTRuCT will be able to complete high-quality large scale stroke trials which are relevant globally. REGISTRATION: URL: http://www.ctri.nic.in/; Unique Identifier: CTRI/2017/05/008507.

Common functional localizers to enhance NHP & cross-species neuroscience imaging research.

Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study.

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies.

Streamlining the institutional review board process in pragmatic randomized clinical trials: challenges and lessons learned from the Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness (ADAPTABLE) trial.

BACKGROUND: New considerations during the ethical review processes may emerge from innovative, yet unfamiliar operational methods enabled in pragmatic randomized controlled trials (RCT), potentially making institutional review board (IRB) evaluation more complex. In this manuscript, key components of the pragmatic "Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE)" randomized trial that required a reappraisal of the IRB submission, review, and approval processes are discussed. MAIN TEXT: ADAPTABLE is a pragmatic, multicenter, open-label RCT evaluating the comparative effectiveness of two doses of aspirin widely used for secondary prevention (81 mg and 325 mg) in 15,000 patients with an established history of atherosclerotic cardiovascular disease. The electronic informed consent form is completed online by the participants at the time of enrollment, and endpoint ascertainment is conducted through queries of electronic health records. IRB challenges encountered regarding centralized IRB evaluation, electronic informed consent, patient engagement, and risk determination in ADAPTABLE are described in this manuscript. The experience of ADAPTABLE encapsulates how pragmatic protocol components intended to facilitate the study conduct have been tempered by unexpected, yet justified concerns raised by local IRBs. How the lessons learned can be applied to future similar pragmatic trials is delineated. CONCLUSION: Development of engaging communication channels between IRB and study personnel in pragmatic randomized trials as early as at the time of protocol design allows to reduce issues with IRB approval. Integrations of the lessons learned in ADAPTABLE regarding the IRB process for centralized IRBs, informed consent, patient engagement, and risk determination can be emulated and will be instrumental in future pragmatic studies.

Strategies for the use of Ginkgo biloba extract, EGb 761® , in the treatment and management of mild cognitive impairment in Asia: Expert consensus.

BACKGROUND: Mild cognitive impairment (MCI) is a neurocognitive state between normal cognitive aging and dementia, with evidence of neuropsychological changes but insufficient functional decline to warrant a diagnosis of dementia. Individuals with MCI are at increased risk for progression to dementia; and an appreciable proportion display neuropsychiatric symptoms (NPS), also a known risk factor for dementia. Cerebrovascular disease (CVD) is thought to be an underdiagnosed contributor to MCI/dementia. The Ginkgo biloba extract, EGb 761® , is increasingly being used for the symptomatic treatment of cognitive disorders with/without CVD, due to its known neuroprotective effects and cerebrovascular benefits. AIMS: To present consensus opinion from the ASian Clinical Expert group on Neurocognitive Disorders (ASCEND) regarding the role of EGb 761® in MCI. MATERIALS & METHODS: The ASCEND Group reconvened in September 2019 to present and critically assess the current evidence on the general management of MCI, including the efficacy and safety of EGb 761® as a treatment option. RESULTS: EGb 761® has demonstrated symptomatic improvement in at least four randomized trials, in terms of cognitive performance, memory, recall and recognition, attention and concentration, anxiety, and NPS. There is also evidence that EGb 761® may help delay progression from MCI to dementia in some individuals. DISCUSSION: EGb 761® is currently recommended in multiple guidelines for the symptomatic treatment of MCI. Due to its beneficial effects on cerebrovascular blood flow, it is reasonable to expect that EGb 761® may benefit MCI patients with underlying CVD. CONCLUSION: As an expert group, we suggest it is clinically appropriate to incorporate EGb 761® as part of the multidomain intervention for MCI.

Regulatory and operational challenges in conducting Asian International Academic Trial for expanding the indications of cancer drugs.

There are many differences between Asian regions in terms of the regulatory requirements and operational procedures in conducting international academic clinical trials for the approval of new drugs. The National Cancer Center Hospital in Japan has launched an international investigator-initiated registration-directed trial (IIRDT) in Japan, Korea, Taiwan, and Singapore, aiming at obtaining pharmaceutical approval in participating regions. Differences in regulatory and operational procedures were identified while coordinating the trial. In Japan, regulatory authority reviews should be performed after approval by institutional review boards for IIRDT, whereas in other regions these can be done in parallel. There were disparities in Good Manufacturing Practice-related documents between regions. Several differences were found regarding investigational product (IP) management, specifically concerning labeling, import/export procedures, and customs clearance costs. On the other hand, safety reporting procedures were relatively well-harmonized in accordance with International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use, Clinical Safety Data Management: Definitions and Standards for Expedited Reporting (ICH-E2A). Regions also differed in per-patient costs, due to varying regulations for academic registration-directed trials. In conclusion, the observed differences among Asian regions should be harmonized to facilitate international academic trials in Asia and thus resolve unmet patient needs worldwide. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? International clinical trials have become common because they make it possible to accrue patients faster and obtain new drug approval in wider areas. However, pharmaceutical regulatory differences hinder the efficient conduct of international clinical trials, especially in academia. WHAT QUESTION DID THIS STUDY ADDRESS? We conducted an academic international clinical trial on new drug applications in four Asian countries and clarified pharmaceutical regulatory differences and operational difficulties. WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? The study identified differences between countries in terms of regulatory affairs, institutional review board (IRB) review processes, investigational new drug (IND) dossiers, investigational product (IP) management procedures, and clinical trial costs, while safety reporting procedures were relatively harmonized. Japan utilizes investigator-initiated registration-directed trials, an advanced regulatory system for new drug application by academia, but the other countries do not. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? Harmonization of pharmaceutical regulations and trial initiation procedures, and regulatory reform of clinical trial costs are important to accelerate academic international clinical trials for new drug applications.

Utility-Weighted Modified Rankin Scale Scores for the Assessment of Stroke Outcome: Pooled Analysis of 20 000+ Patients.

BACKGROUND AND PURPOSE: Patient-centered care prioritizes patient beliefs and values towards wellbeing. We aimed to map functional status (modified Rankin Scale [mRS] scores) and health-related quality of life on the European Quality of Life 5-dimensional questionnaire (EQ-5D) to derive utility-weighted (UW) stroke outcome measures and test their statistical properties and construct validity. METHODS: UW-mRS scores were derived using linear regression, with mRS as a discrete ordinal explanatory response variable in 8 large international acute stroke trials. Linear regression models were used to validate UW-mRS scores by assessing differences in mean UW-mRS scores between the treatment groups of each trial. To explore the variability in EQ-5D between individual mRS categories, we generated receiver operator characteristic curves for EQ-5D to differentiate between sequential mRS categories and misclassification matrix to classify individual patients into a matched mRS category based on the closest UW-mRS value to their observed individual EQ-5D value. RESULTS: Among 22 946 acute stroke patients, derived UW-mRS across mRS scores 0 to 6 were 0.96, 0.83, 0.72, 0.54, 0.22, -0.18, and 0, respectively. Both UW-mRS and ordinal mRS scores captured divergent treatment effects across all 8 acute stroke trials. The sample sizes required to detect the treatment effects using UW-mRS scores as a continuous variable were almost half that required in trials for a binary cut point on the mRS. Area under receiver operator characteristic curves based on EQ-5D utility values varied from 0.66 to 0.81. Misclassification matrix showed moderate agreement between actual and matched mRS scores (kappa, 0.68 [95% CI, 0.67-0.68]). CONCLUSIONS: Medical strategies that target avoiding dependency may provide maximum benefit in terms of poststroke health-related quality of life. Despite variable differences with mRS scores, the UW-mRS provides efficiency gains as a smaller sample size is required to detect a treatment effect in acute stroke trials through use of continuous scores. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT00226096, NCT00716079, NCT01422616, NCT02162017, NCT00120003, NCT02123875. URL: http://ctri.nic.in; Unique identifier: CTRI/2013/04/003557. URL: https://www.isrctn.com; Unique identifier: ISRCTN89712435.

Improving the evaluation of COPD exacerbation treatment effects by accounting for early treatment discontinuations: a post-hoc analysis of randomized clinical trials.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) clinical trials aimed at evaluating treatment effects on exacerbations often suffer from early discontinuations of randomized treatment. Treatment discontinuations imply a loss of information and should ideally be considered in the statistical analysis of trial results, particularly if the discontinuations are related to the disease or treatment itself. Here, we explore this issue by investigating (1) whether there exists an association between the risks of exacerbation and treatment discontinuation in COPD clinical trials and (2) whether disregarding this association can cause bias in exacerbation treatment effect estimates. We focus on the hypothetical estimand, i.e. the treatment effect that would have been observed had all subjects completed the trial as planned. METHODS: The association between exacerbation and discontinuation risks was analysed by applying a joint frailty (random effect) model - allowing for the simultaneous analysis of multiple types of correlated events - to data from five Phase III-IV COPD clinical trials. Specifically, the impact of the association on exacerbation treatment effect estimates was assessed by comparing the treatment hazard ratios of the joint frailty model to the rate/hazard ratios of two related statistical models (the negative binomial and shared frailty models), which both assume discontinuations to be unrelated to the trial outcome. The models were also compared using simulated data. RESULTS: A statistically significant (p < 0.0001), positive association between exacerbation and discontinuation risks was found in all trials. Importantly, simulations confirmed that - with such an association - models disregarding the association risk producing biased results (> 5 percentage point difference in hazard/rate ratio). For some treatment comparisons in the clinical trials, the difference in treatment effect estimates between the joint frailty and the other models was as high as 10-15 percentage points. The difference was affected by the strength of the exacerbation-discontinuation association, the population heterogeneity in exacerbation risk, and the difference in discontinuation rates between treatment arms. CONCLUSIONS: We have identified an association between the risks of exacerbation and treatment discontinuation in five COPD clinical trials. We recommend using the joint frailty model to account for this association when estimating exacerbation treatment effects, particularly when targeting the hypothetical estimand.

Considerations for Integration of Perioperative Electronic Health Records Across Institutions for Research and Quality Improvement: The Approach Taken by the Multicenter Perioperative Outcomes Group.

Use of the electronic health record (EHR) has become a routine part of perioperative care in the United States. Secondary use of EHR data includes research, quality, and educational initiatives. Fundamental to secondary use is a framework to ensure fidelity, transparency, and completeness of the source data. In developing this framework, competing priorities must be considered as to which data sources are used and how data are organized and incorporated into a useable format. In assembling perioperative data from diverse institutions across the United States and Europe, the Multicenter Perioperative Outcomes Group (MPOG) has developed methods to support such a framework. This special article outlines how MPOG has approached considerations of data structure, validation, and accessibility to support multicenter integration of perioperative EHRs. In this multicenter practice registry, MPOG has developed processes to extract data from the perioperative EHR; transform data into a standardized format; and validate, deidentify, and transfer data to a secure central Coordinating Center database. Participating institutions may obtain access to this central database, governed by quality and research committees, to inform clinical practice and contribute to the scientific and clinical communities. Through a rigorous and standardized approach to ensure data integrity, MPOG enables data to be usable for quality improvement and advancing scientific knowledge. As of March 2019, our collaboration of 46 hospitals has accrued 10.7 million anesthesia records with associated perioperative EHR data across heterogeneous vendors. Facilitated by MPOG, each site retains access to a local repository containing all site-specific perioperative data, distinct from source EHRs and readily available for local research, quality, and educational initiatives. Through committee approval processes, investigators at participating sites may additionally access multicenter data for similar initiatives. Emerging from this work are 4 considerations that our group has prioritized to improve data quality: (1) data should be available at the local level before Coordinating Center transfer; (2) data should be rigorously validated against standardized metrics before use; (3) data should be curated into computable phenotypes that are easily accessible; and (4) data should be collected for both research and quality improvement purposes because these complementary goals bolster the strength of each endeavor.

Stability of mismatch negativity event-related potentials in a multisite study.

OBJECTIVES: Mismatch negativity (MMN), an auditory event-related potential sensitive to deviance detection, is smaller in schizophrenia and psychosis risk. In a multisite study, a regression approach to account for effects of site and age (12-35 years) was evaluated alongside the one-year stability of MMN. METHODS: Stability of frequency, duration, and frequency + duration (double) deviant MMN was assessed in 167 healthy subjects, tested on two occasions, separated by 52 weeks, at one of eight sites. Linear regression models predicting MMN with age and site were validated and used to derive standardized MMN z-scores. Variance components estimated for MMN amplitude and latency measures were used to calculate Generalizability (G) coefficients within each site to assess MMN stability. Trait-like aspects of MMN were captured by averaging across occasions and correlated with subject traits. RESULTS: Age and site accounted for less than 7% of MMN variance. G-coefficients calculated at electrode Fz were stable (G = 0.63) across deviants and sites for amplitude measured in a fixed window, but not for latency (G = 0.37). Frequency deviant MMN z-scores averaged across tests negatively correlated with averaged global assessment of functioning. CONCLUSION: MMN amplitude is stable and can be standardized to facilitate longitudinal multisite studies of patients and clinical features.

Development and reliability of questionnaires for the assessment of diet and physical activity behaviors in a multi-country sample in Europe the Feel4Diabetes Study.

BACKGROUND: Assessment of diet and physical activity and their determinants still remains a demanding task, especially when the objective is to evaluate the efficacy of lifestyle interventions. In the context of the Feel4Diabetes study (a European community based intervention study in families with school aged children and at high risk of developing diabetes), we aimed to develop questionnaires for the assessment of food-frequency and eating behaviors, and physical activity and sedentary behaviors in both parents and school-aged children and a questionnaire for overall family's energy balance-related behaviors. METHODS: Questionnaires were developed to be used in 6 countries under standardized harmonization procedures and included questions regarding not only food intake and physical activity, but also questions of their determinants. A reliability study was conducted in 191 pairs of parents and their children (N = 191). Parents completed the questionnaires on two occasions, within a 1-2 week interval. Reliability was tested by the intra-class correlation coefficients (ICC) of test-retest. RESULTS: Most of the questions in all questionnaires had excellent reliability, assessed as an ICC of > 0.810. Mean ICCs for food-frequency and eating behaviors questionnaires were 0.838 and 0.787, and for physical activity and sedentary behaviors questionnaires were 0.734 and 0.793, in adults and children respectively. Mean ICC for overall family's energy balance-related behaviors and their determinants was 0.659. CONCLUSION: The developed questionnaires showed acceptable reliability and may be valuable tools in the assessment of children's and parents' behaviors related to diet, physical activity, sedentary behavior and overall energy balance in school- and community-based interventions.

International multicenter examination of MOG antibody assays.

OBJECTIVE: To compare the reproducibility of 11 antibody assays for immunoglobulin (Ig) G and IgM myelin oligodendrocyte glycoprotein antibodies (MOG-IgG and MOG-IgM) from 5 international centers. METHODS: The following samples were analyzed: MOG-IgG clearly positive sera (n = 39), MOG-IgG low positive sera (n = 39), borderline negative sera (n = 13), clearly negative sera (n = 40), and healthy blood donors (n = 30). As technical controls, 18 replicates (9 MOG-IgG positive and 9 negative) were included. All samples and controls were recoded, aliquoted, and distributed to the 5 testing centers, which performed the following antibody assays: 5 live and 1 fixed immunofluorescence cell-based assays (CBA-IF, 5 MOG-IgG, and 1 MOG-IgM), 3 live flow cytometry cell-based assays (CBA-FACS, all MOG-IgG), and 2 ELISAs (both MOG-IgG). RESULTS: We found excellent agreement (96%) between the live CBAs for MOG-IgG for samples previously identified as clearly positive or negative from 4 different national testing centers. The agreement was lower with fixed CBA-IF (90%), and the ELISA showed no concordance with CBAs for detection of human MOG-IgG. All CBAs showed excellent interassay reproducibility. The agreement of MOG-IgG CBAs for borderline negative (77%) and particularly low positive (33%) samples was less good. Finally, most samples from healthy blood donors (97%) were negative for MOG-IgG in all CBAs. CONCLUSIONS: Live MOG-IgG CBAs showed excellent agreement for high positive and negative samples at 3 international testing centers. Low positive samples were more frequently discordant than in a similar comparison of aquaporin-4 antibody assays. Further research is needed to improve international standardization for clinical care.